Meta or better data?The value of user profiling for information services

Stephen NortheyProduct Development Manager

Optimus Prime Pty Ltdstephen@optimus-prime.com

and

Bill FatourosExecutive Director

Optimus Prime Pty Ltdbill@optimus-prime.com

Abstract:The increased use of information technology and ‘meta data’ standards have resulted in areduction in the competitive advantage gained from the application of traditional ‘meta-data’elements, despite the continued importance of this practice. Without effective user profilingthat allows information systems to match information with people, practice and strategy, thecontent expectations of these systems will inevitably fall short. Application of an extendedrange of ‘meta data’ elements can assist information services to differentiate their productsand services in the market place, create a knowledge profile for their organisation and bettertarget the delivery of services for competitive advantage. User profiles then become valuableinformation objects in themselves that allow users to locate expertise within an organisationand allow information services to position information within practice communities andstrategic context.

Meta or better data?The value of user profiling for information services

Consider this …

How well an organisation does in acquiring and applying knowledge will become a keycompetitive factor. Peter Drucker (1994)

For information to become knowledge, it must incorporate relationships between ideas. R.Kurzweil (1990)

There can be no knowledge without emotion. We may be aware of a truth, yet until we havefelt its force, it is not ours. To the cognition of the brain must be added the experience of thesoul. Arnold Bennett (1876-1931)

The aim of knowledge management is for businesses to become more competitive throughthe capacities of their people to be more flexible and innovative. Marianne Broadbent (1998)

1. Our rationale

The purpose of this paper is to outline the potential benefits for information services inapplying an extended meta data set to profile information service clients. There is anincreasing need for libraries to identify the needs and expertise of their clients in order tobecome knowledge agents within their organisations and prosper in a highly competitiveknowledge economy. The model proposed in this paper provides opportunities for libraries toshift from a valuable (but disposable) resource to a central organ within the modernorganisation.

As system designers, our vision is a more holistic knowledge support technology centred onan information management framework that supports the relationship between recordedknowledge (information), people and the processes used to achieve organisational goals. Thisrequires us to re-think the use of our library management systems in terms of the data wemaintain on our clients.

2. What is meta data?

In simplistic terms, meta data is data about data. Meta data allows us to identify meaning,context and validity of data. Meta data provides a set of knowable facts about the structure,organisation and behaviour of a given set of data.

Meta data plays a vital role in data quality processes. The more information (or meta data)you are given about a piece of data, the more value you can derive from the data. When littleor no meta data is provided it is difficult to determine the validity of the data - you don’tknow enough about the data to reliably use it. (Forino, 2000)

The term meta data has different connotations depending on the field of application. From aninformation management perspective, meta data may refer to the attribute descriptors appliedfrom standards such as Dublin Core or XML schemas. On the other hand, meta data from an

information systems perspective may refer to attributes required for data integration andtransfer activities involved in a data warehouse project. This paper uses both understandingsof meta data - firstly in advocating for a richer description of information content and context,and secondly, in advocating for organisational standards to enable integration of multiple datasources.

The primary purpose of applying meta-data is to improve access to and interpretation of theinformation being described. In library terms, meta data elements such as subject headings,keywords and classification codes provide opportunities to place an information object withinthe subject context of other information objects.

In current library systems, meta data is also used to dissemination information. SelectiveDissemination of Information (SDI) uses a meta data match between subject data on acatalogue record and subject data (statement of interests) on a patron record. Meta data is alsocollected on loan, reservation and route transactions associated with particular patron metadata profiles.

Rules governing business processes are typically encoded into the library system to define theparameters of these transactions, such as the number of days a loan is issued for, and totrigger actions, such as an email alert, based on some criteria, such as a match betweensubject data on a catalogue record and the statement of interests on a patron record.

Looking at the relationship between people, information and these matching processes is auseful way of exploring the opportunities for information services to improve the level ofservice they provide to their clients.

Diagram 1 - The relationship between people, information and processes

The diagram below illustrates the relationship between people, information and processessupported by most current library management systems.

Diagram 2 - A current view library management system support

3. Limitations of current library management systemsInformation acts as a stimulus to knowledge. People respond differently to any given objectof information based on the integration of the information within a pre-existing set ofconcepts, interpretations and assumed relationships. On one level, knowledge is defined asinternalised information. (Meredith and Burstein, 2000)

Current library systems do little to stimulate knowledge. Current systems are ‘information-centric’. The following diagram indicates the type of meta data associated with an‘information-centric’ system.

PEOPLE

INFORMATION PROCESSES

Apply

Informs

Define

Alert

TriggersDisseminate

Diagram 3 – An ‘information-centric’ approach to meta data

Current library systems provide an excellent tool for storing and organising meta data oninformation objects. Often they provide efficient search engines for retrieving informationbased on sophisticated meta data definition. However, current library systems do little to pushthe right information out to the right users in an effort to stimulate the knowledge acquisition,creation and sharing processes.

These systems more often than not rely on end users to take responsibility for defining andmaintaining their information requirements and knowledge deficits. It is reasonable to

DescriptiveAttributesID (RecordNumber)TitleEditionPhysical descriptionPublisherYear

INFORMATION OBJECT

Topical AttributesSubjectKeywords

Location AttributesCall NumberLocationBarcodeURL

Authority AttributesType (Author, Subject)TermRelationships(BT, NT, RT, Use, UF)Type (Subject)

AUTHORITY

Content AttributesAbstractNotes

Identity AttributesUser IdUser Name

PEOPLE OBJECT

Contact AttributesAddressPhoneFaxEmail

TransactAttributesLoansReservations

SDI AttributesSubject

question whether the current practice of information management inherent in the design andapplication of library systems really has the capacity to support knowledge processes.

If we consider our information/people/process model and the circular relationship betweenpeople and information, information and processes, and processes and people, we can see thatthe eddy created between each relationship is weak.

Even our much-celebrated Selective Dissemination of Information (SDI) technology haslimitations. The main problem with SDI is the reliance on users to keep profiles up-to-date.Allowing users to select from group profiles based on the concept of stereotypes is onesolution to these problems. (Broadbent and Lofgren, 1993; Rich, 1989)

SDIs are, however, still confined to benefiting the individual user to whom the model/profilebelongs. The user profile is used to enrich or tailor that user’s interaction with the system butnot as an item, which might be of interest to other users. The user is not treated as object ofinformation retrieval. (Harvey, Smith and Lund, 1998) Further, user profiles are rarely usedas a way of validating information objects stored in the system.

There are a number of emergent trends in the current business environment that impactsignificantly on the sustainability of this approach to information management.

4. Five key trends affecting the sustainability of the currentapproach

4.1 Reduction in competitive advantage achieved from traditional approach

(a) Information Technology is increasingly more affordable and accessible: Inthe past, information technology and data processing power were expensive.Competitive advantage was gained by investment in technology that supportedsystems others in the market place could not afford. Today, more and morepeople have access to networks and personal computers.

(b) A plethora of online resources is more affordable and accessible: As a resultof the affordability and accessibility of technology, a plethora of online resourceshas emerged. Access to these resources is increasingly delivered via the Internet.It was only recently that public users had full access to the entire EncyclopaediaBritannica via the Internet. Simply put, companies everywhere have access toessentially the same information (Buchanan, 1995) thereby obviating competitiveadvantage.

(c) More refined use of meta data has increased access to information: With theexplosive growth in the complexity of information management throughout oursociety the types of meta data applied to information objects have expanded.Malcolm Chisholm in his article “Is the meta data repository dead?” states thatthe goal of being able to completely define the meta data for a given database israpidly receding, although it is very unlikely that we have reached a stage whereno new types of meta data will appear. (Chisholm, 2001) The emergence of theDublin Core Initiative to cope with the explosion of online information resourcesis further evidence of this trend.

4.2 Information is no longer utilised and managed in a physical library

(a) Departments increasingly create, acquire and manage information: By theend of 20th century, computer-based systems had given individuals access to anenormous network of information. Knowledge was increasingly recognised as thefourth resource in building post-war economies. As a result, concern forhusbanding knowledge resources has extended from the traditional library andarchive to encompass organisational, institutional and governmental information.

(b) Increasing availability of information in electronic format: IT has functionedin a similar way as the introduction of the printing press in dramaticallyincreasing the publication and distribution of information. The importance ofcurrency in a rapidly changing business environment means more and moreinformation is published and quickly disseminated in electronic format.Production cost is also a factor here.

(c) IT driven intranets and portals are replacing libraries as informationcentres: With the increase in information stored in electronic format, ITdepartments have increasingly adopted responsibility for the provision ofinformation services, essentially via intranets. The importance of ‘meta-data’ hasbecome more apparent as data warehousing and data-mining initiatives havebecome more widespread. Content on intranets and in data warehouses hasexploded and IT departments have began to face similar challenges to those facedby library science during the 19th century, principally the need to filter and deliverrelevant information to end-users. The development of corporate informationportals is a technological response to this challenge.

4.3 Knowledge management has changed the notion of the role ofinformation management and the library

(a) Value shift from information access to access to the knowledge of people: In aknowledge-driven society there are two key assets to manage, namely thecompetitive information an organisation possesses and the individual whoincreases the value of information by adding experience, knowledge andassociations in order to produce other, even more valuable information.(Anderbjörk, 1999) Given organisations everywhere have access to essentially thesame information, (Buchanan, 1995) the value of knowledge becomes critical tobusiness success in terms of building competitive advantage.

(b) Information requires a more direct relationship with business strategy: Froma business perspective, information only realises its potential value when appliedwithin the context of a situation or problem. People prefer contextual information,synthesised from multiple sources and providing implications and interpretationsrather than mere facts. (Davenport, 1997)

(c) Information systems need to stimulate knowledge creation and sharing:Given the importance of information within the context of business strategy,information systems increasingly require functionality that allows people torecord their thoughts (cognitive responses), emotions (affective responses) andactions (conative responses) associated with their experience of objects of

information. (Meredith, May and Piorun, 2000; Schauder, 2000) Sharedthroughout a community, this knowledge or meta-knowledge (Schauder, 2000)stimulates more knowledge and adds value to the overall knowledge assets of anorganisation.

4.4 End users increasingly demand more relevant information within context

(a) Relationships between ideas are required to assist knowledge transfer: Forinformation to become knowledge, it must incorporate the relationships betweenideas or concepts. Transferring this knowledge requires that the attributes used todescribe how concepts interact are easily accessible, updated, and manipulated.(Kurzweil, 1990)

(b) Data about application of information is increasingly more important:Learning is critical in a knowledge culture. People learn from personal and socialexperience. People often seek out other people who may have already appliedinformation in a given situation. This is why ‘word-of-mouth’ and informal‘coffee-room’ exchanges are emphasised in marketing and knowledgemanagement theory respectively.

(c) Information is increasingly relevant to more specialised groups within anorganisation: In his sentinel 1994 article “The Age of social transformation”,Peter Drucker predicted that the central workforce in the knowledge society willconsist of highly specialised people and that applied knowledge is effective onlywhen it is specialised. (Drucker, 1994)

4.5 End users have less time to search and process available information

(a) Information glut affects performance: ‘Info glut’, the overwhelmingavailability of information and data, has begun to measurably affect productivity.Organisations that understand how to navigate the information flood will have adistinct advantage over their competitors. Personalisation features andtaxonomies can ease access to relevant information. (Linden and Jacobs, 2001)

(b) Experts are the best agents for filtering information for relevancy andutility: The use of people or experts as an index to information is one way tocope with the information overload phenomenon. (Harvey, Smith and Lund,1998)

(c) Information presentation and peer review decreases information processingtime: Recall and precision (the number and relative quality of items retrieved) arethe two key performance measures traditionally used to evaluate informationretrieval systems. (Russom, 1999) Information systems usually perform betterthan people in maximising recall. However, where precision is required, peopleoften consult perceived experts or likely ‘knowledge holders’ in relation to thebest information. The information seeker uses the intuition, perceptions anddiscrimination of the expert to retrieve the required information. (Harvey, Smithand Lund, 1998) However, increased information often leads to negative selectiondecisions (Thomas, 2000), and therefore reduces precision. Better, fasterdecisions can provide organisations with a significant advantage in a competitiveenvironment. (Russom, 1999)

Again, looking at the relationship between people, information and processes we can quicklysee tremendous opportunities for information services to improve the level of service theyprovide to their clients. The diagram below illustrates a much richer relationship betweenpeople, information and processes.

Diagram 4 – Opportunities for library management system support

Clearly, there is pregnant opportunity to vitalise the relationship, from a system perspective,between people, information and processes. However, a number of trends in the technologyand service market should be considered as we contemplate a design for futurelibrary/information management systems.

PEOPLE

INFORMATION PROCESSES

CreateApplyAssociateEvaluate

InformsStimulatesIdentifiesVerifies

DefineCustomise

AlertAssociateManage

TriggersInformsModifies

StructureFilterRankValidateDisseminateUpdate

5. Five Key trends affecting the design of future approaches

5.1 Trend away from a single meta data repository towards an integratedmodel of distributed databases

(a) Explosive growth in the complexity of information management: Accordingto a number of data-warehousing experts, the goal of being able to completelydefine the meta data for a given database is rapidly receding. (Chisholm, 2001;Dresner, 2001, Hurwitz Group, 1998; Jennings, 2001)

(b) Increase in volume of highly specialised data processing needs: Asinformation becomes a more important corporate resource the demand to manageit increases. As a consequence there is a need for quite disparate kinds of metadata. Meta data is increasingly too diverse to support the notion that there can beone repository to store all meta data. (Chisholm, 2001)

(c) Implementation of industry wide meta data standards and data mappingbetween multiple repositories: Next generation databases are moving from alarge, centralised data warehouse model to one characterised by small,distributed, application-specific databases. A distributed architecture requiresdatabases share common keys and attributes. In other words, meta dataconsistency is a key issue where multiple repositories are distributed across theenterprise. Currently, the largest cost associated with metadata is that ofreplication and coordination. (Hulser, 1998)

The diagram below illustrates an integrated meta data repository model.

Diagram 5 – An integrated meta data repository model

Data Store#1

Data Store#2

Data Store#3

BU

SIN

ES

S R

UL

ES

(for

dat

a ab

stra

ctio

n)

USERS

BU

SIN

ES

S A

PP

LIC

AT

ION

S

5.2 Increasing need to change business rules quickly and cost effectively in arapidly changing environment

(a) Rules governing business process change regularly and rapidly: The rulesgoverning business processes constantly change. (Johnston, 2001) Addressingthese changes is far easier and more cost effective at the meta data level than atthe data level.

(b) Hard-coded business rules are expensive and time consuming to change:Systems become increasingly redundant if they lack the flexibility to incorporatechanges to business processes quickly and cost-effectively.

(c) Business rules are more efficiently managed from the interface: Staffresponsible for service delivery need to alter the parameters of systems from theinterface level in order for systems to remain relevant to specific business goals.

5.3 Strong trend towards user authentication to secure and manage accessto information products and services

(a) Increased ability to access and distribute information invariably meansorganisations will need to restrict access where commercial-in-confidence orconflict of interest conditions apply.

(b) Privacy issues are associated with providing public access to user data:Research indicates that individuals need to feel they have control of the content oftheir profiles to avoid systems being regarded as spying and therefore arousinghostility. (Harvey, Smith and Lund, 1998) Protecting the user’s personalinformation is not just a courtesy: it is a legal obligation. (Rothman, 2000)Privacy of employee details within the organisation may indeed become a majorcivil liberty issue in the future.

(c) Increase in delivery of commercial information products and services:Organisations who value the knowledge of their people and view theirinformation as a corporate resource are beginning to package these resources ascommercial online services.

5.4 Emphasis on profiling users to better match information needs anddeliver tailored products and services

(a) ‘Information overload’ necessitates information filtering: The proliferation ofavailable information, coupled with a relative decrease in the amount of free timeavailable to process information, means both specialist and non-specialist demandinformation services that filter-out information less likely to impact on thedecision-making process. Data filtering requires an emphasis on analysinginformation in the context of an organisation’s business environment.

(b) People’s knowledge, and therefore information needs, are becoming morespecialised: Knowledge has to be highly specialised to be productive. Therefore,people increasingly work in expert teams, groups or communities. (Drucker,1994) In other words, people are associated with specialist practice areas. The

information management challenge in building and managing these ‘intelligentcommunities’ is to embed relevant business structures or practice areas ininformation that exists in the form of organised communication or documents.(Anderbjörk, 1999)

5.5 Increasing need to located and verify expertise and peer reviewedinformation

(a) User profiles as an object of information retrieval: Currently, the user profileis used to enrich or tailor that user’s interaction with the system, but not as anitem which might be of interest to other users. The user is not treated as object ofinformation retrieval. (Harvey, Smith and Lund, 1998) User profiles can,however, represent the reputation and expertise of the user it describes.

(b) People are excellent agents for filtering, summarising and directinginformation: To improve the precision of search results, users require enoughdata to enable an evaluation of information retrieved. Common factors used tojudge relevance include topicality, peer interest, novelty, currency andconvenience. (Wang, Hark and Tenopir, 2000)

(c) Peer review increases precision in information retrieval: Typically, theposition a person holds in an organisation provides an indication of the relativevalue assigned to any advice or knowledge contributed by that person. Theacceptance of information often depends on who collects and analyses it, andsome executives consistently rate the findings of high-priced consultants abovethose of an underling or colleague. (Buchanan, 1995) Associating informationwith peer reviews allows users to access and sort critical information vetted bypractice area specialist.

In the context of these trends, there is a clear demand for more people-centric rather thaninformation-centric information management practices. The following diagram proposes arange of meta data attributes relevant for a ‘people-centric’ system.

Diagram 6 – A ‘people-centric’ approach to meta data

Identity AttributesUser IdUser NameType

Contact AttributesAddressPhoneFaxEmail

TransactionalAttributesLoansReservationsRouteSDI AttributesSubject

Association AttributesGroup (Circulation)EmployerProfessionalAssociations

ClientsPractice Area(Expertise)Projects

Reputation AttributesPositionProfessional ProfilePublication

Comment (Advice/Opinion)

INFORMATION OBJECT

Review AttributesCommentType(Response/Action)

Topical AttributesPractice AreasProjects

DescriptiveAttributes

Title

AuthorityAttributes

Type (Author)

Type (Subject)

Type (Author)Type (Author)Type (Author)Type (PracticeArea)Type (Projects)

PEOPLE OBJECT AUTHORITY

6. The benefits of a “people-centric” approach

6.1 We can identify our users: Authenticating users allows an information service toidentify the individual user and deliver services and document access privileges thatmatch that users’ profile. Knowing who the user is also allows information services tocollect and analyse system usage and information retrieval patterns specific to the userand identified groups of users to assist the information service in targeting trainingprograms, modifying system interfaces, identifying opportunities for new products andservices, justifying budget expenditure, identifying redundancies and locating centres ofexpertise.

6.2 We can locate expertise: User profiles provide a valuable object of informationretrieval when attempting to locate expertise within an organisation. User profiles maybe searched directly based on matching meta data defined in a search or retrievedtogether along with relevant information resources in a topical search.

6.3 We can evaluate claims of expertise: Users can evaluate an expert’s profile based onthe meta data description of that person’s professional profile, position, practice areas,project and client involvements as well as linkages to publications and commentsauthored by that user.

6.4 We can position information and people within our business structure:Categorising users and information objects by business specific structures, such aspractice areas, allows an information service to build dynamic path finders comprisingkey information resources and experts in each defined business practice area. Thisremoves the time consuming activity of manually updating static web pages oftenmaintained for this purpose. Categorising users and information objects by practiceareas also allows an information service to define automated alerting services to notifyusers of new material and comments relevant to the practice areas defined on their userprofile.

6.5 We can position information and people within our business activity: Associatingusers and information objects with projects allows an information service todynamically manage issues of commercial-in-confidence and conflict of interest as wellas build structured webs of organisational experience. Projects can then be reviewedwithin the context of information resources employed, people involved and reflectivecomments added by project participants. Again, automated alerting services may bedefined to communicate developments to relevant parties.

6.6 We can associate information and people with our customers: Associatingorganisational staff with business clients allows staff to identify other people within theorganisation who have had dealings with particular clients, and provides those staffwith an opportunity to add comments in relation to those dealings and therefore build adynamic profile of the organisation’s experience with each client.

6.7 We can rank and filter user contributions by ‘standing’ in the business: Recordingthe position a person holds in an organisation provides information services with ameans of ranking or filtering any comments that a person makes in accordance with thevalue associated with the contributor’s position. Search results may also be filtered bymaterial reviewed by people in more senior positions.

6.8 We can add competitive value to information resources: The ability to positioninformation within the context of practice areas and projects, and annotate informationobjects with meta knowledge related to use, experience an/or actions, adds specificorganisational value to information objects that is not available to competitors. In otherwords, user profiling allows an organisation to marry information and knowledgeresources.

6.9 We can improve the currency and relevance of information resources: Includingusers within the author authority file structure allows an information service to manageinternally produced documents in the same way as other information objects. Thisallows a direct linkage from a patron record to authored publications, which can assistthe evaluation of expertise. Any comments attached to an authored document byanother user can also trigger feedback to the author in relation to inaccuracies,contradictory evidence or emerging developments that may affect content or futureusage.

6.10 We can personalise the information service desktop: With the enhanced ability topackage information and define more specific business rules based on an extended metadata set, information services can also offer a range of products that can be embeddedin corporate portal applications. This allows users to personalise their own informationservice desktop.

All of these benefits are specific to the business and are therefore defined in businessprocesses. Processes can automate many of the transactions involved in delivering thesebenefits. The diagram below illustrates some the processes possible in ‘people-centric’systems.

7. Using processes to match people with information

Diagram 7A – Processes matching people with information

ActionObject Filtering

INFORMATIONOBJECT

PROCESSES

Identity AttributesUser IdTypeAssociation AttributesGroup (Circulation)EmployerClientsPractice Area (Expertise)Projects

PATRON OBJECT

AccessProcessesAuthenticationObject Exclusion

ActionFunction AccessObject Access

CirculationProcessesLoanReservationRoutingOverdue LoanReservation CancelReservation Pickup

Identity AttributesUser Id

Association AttributesGroup (Circulation)Employer

Transactional AttributesMaximum LoansLoan PeriodMaximum RenewalsMaximum Reservations

ActionCirculation

Current AwarenessRecent AcquisitionsSDI Alert

Identity AttributesUser Id

Association AttributesGroup (Circulation)EmployerClientsPractice Area (Expertise)Projects

Reputation AttributesPosition

SDI AttributesSubject

Diagram 7B – Processes matching people with information

Feedback ProcessesComment AlertsVerificationPeer Review

Association AttributesPractice Area (Expertise)

SDI AttributesSubject

INFORMATION OBJECT PROCESSES

Identity AttributesType

Association AttributesPractice Area (Expertise)Projects

PATRON OBJECT

Structural ProcessesRelationshipReporting

ActionFunction AccessObject AccessObject Filtering

Topical ProcessesRelationship

ActionObject Filtering

Transactional AttributesDate Modified

Update ProcessesUpdate Alert

ActionObject Update

Association AttributesProfessionalAssociationsPractice Area (Expertise)Projects

Reputation AttributesPositionPublicationComment (Advice/Opinion)

Validation ProcessRelevancyExpertiseContribution

ActionObject FilteringObject SortingObject Linkage

Transactional AttributesSearchesObject AccessDownloadsDate/Time

Learning ProcessesProfilingPattern Matching

ActionUsage Statistics

Identity AttributesUser IdUser NameType

Reputation AttributesPositionComment (Advice/Opinion)

ActionObject Update

8. Conclusions

This paper has outlined the benefits of applying an extended meta data set in order to profileusers. These meta data attributes provide a deeper description of the people who collectivelycomprise the knowledge asset of an organisation.

Better data on this asset allows us to match, filter, categorise, evaluate, package anddisseminate information with the specific business requirements of individual people andgroups of people.

The model proposed in this paper provides opportunities for libraries to use their informationmanagement systems to stimulate knowledge processing and become more central to thestrategic direction of the organisations they seek to support.

In summary, this paper concludes:

8.1 The ability for libraries to survive and prosper will depend on their ability to bettermatch information with people.

8.2 User profiling provides a means for libraries to deliver dynamic information productsand services that match the known and potential requirements of individual users andgroups.

8.3 The information needs of people are increasingly aligned with activities directedtowards achieving specific organisational or community goals.

8.4 User profiling provides a means of associating information and expertise (people) withspecific organisational strategies.

8.5 The capacity of people to acquire and apply knowledge, to be more flexible andinnovative, is a key competitive factor.

8.6 User profiling provides a means of associating and sharing experience and locatingknowledge with an organisation.

In short, we need to consider the application of better meta data to meet future dataprocessing requirements and service expectations. Importantly, better application of metadata can significantly increase the competitive advantage derived from an organisation’sknowledge resources.

REFERENCESAnderbjörk, Gabriel, October (1999). Intelligent communities: managing people and

information in the 21st century. Comintell. [Downloaded from www.comintell.com]

Bates, M. J. (1986). ‘Subject access in online catalogs: a design model’ in Journal of theAmerican Society for Information Science 37: pp 357-76.

Bishop, Ann Peterson. (1998). ‘Logins and Bailouts: Measuring Access, Use, and Success inDigital Libraries’ in The Journal of Electronic Publishing 4 (2). [Available fromhttp://www.press.umich.edu/jep/04-02/index.html]

Broadbent, M. (1998). ‘The phenomenon of knowledge management: What does it mean tothe information profession?’ in Information Outlook 2 (5): pp 23-36.

Broadbent, M. and Lofgren, H. (1993). ‘Information delivery: identifying priorities,performance, and value’ in Information Processing and Management. 29 (6): pp.683-701.

Buchanan, Leigh. (1995). ‘Scavenger Hunt’ in CIO Magazine July 1, 1995.[Downloaded from www.cio.com/archive/070195_info_content.html on 31/5/2001]

Chisholm, Malcolm (2001). ‘Is the meta data repository dead?’ in DM Review Online May2001. [Downloaded fromwww.dmreview.com/editorial/dmreview/print_action.cfm?EdID=3335 on 31/5/2001]

Davenport, Thomas H. (1998). ‘Industry insight: from data to knowledge’ in OracleMagazine May 1998. [Downloaded fromwww.oracle.com/oramag/oracle/98-May/ind2.html on 31/5/2001]

__________________. (1997). ‘Processing process information’ in CIO Magazine March 15,1997. [Downloaded from www.cio.com/archive/031597_think_content.html on31/5/2001]

Dresner, H. (2001). ‘The Data warehouse: dead or alive’. Research Note 2 May 2001.Gartner. [[Download from www.gartner.com on 17/7/2001]

Drucker, Peter F. (1994). ‘The Age of social transformation’ in The Atlantic Monthly 274 (5)November 1994: pp 53-80. [Downloaded fromwww.theatlantic.com/politics/ecbig/soctrans.htm on 31/5/2001]

Eifrig, Janice and Roberts, Carol. (1998). ‘Creating an online client information database’.Special Libraries Association, Washington D.C. [Downloaded fromwww.sla.org/pubs/serial/io/1998/jul98/roberts.html on 31/5/2001]

Estabrook, Leigh S. Encyclopedia Britannica Article. Britannica.com. [Downloaded fromhttp://www.britannica.com/eb/article?eu=109616 on 23/07/2001]

Fenn, J and Linden, A. (2001). ‘Hottest of the hot: discontinuities of the next decade’.Research Note, 20 April 2001. Gartner. [Download from www.gartner.com on17/7/2001]

Field, Tom. (1997). ‘Getting in touch with your inner web’ in CIO Magazine 15 January1997. [Downloaded from www.cio.com/archive/011597_intranet_content.html on31/5/2001]

Forino, Ronald. (2000). ‘Data e.Quality: the meta data supply chain’ in DM Review OnlineNovember 2000. [Downloaded from

www.dmreview.com/editorial/dmreview/print_action.cfm?EdID=2522 ]

Hallet, Peter. (2001). ‘Web-based visualization’ in DM Review Online June 2001.[Downloaded fromwww.dmreview.com/editorial/dmreview/print_action.cfm?EdID=3486 ]

Harman, D. (1992). ‘User friendly systems instead of user friendly front ends’ in Journal ofthe American Society of Information Science 43: pp 164-74.

Harvey, Clare F, Smith, Peter and Lund, Peter. (1998) ‘Providing a networked future forinterpersonal information retrieval: InfoVine and user modeling’ in Interacting withComputers 10 1998: pp 195-212.

Hert, C. A. and Marchionini, G. (1998). ‘Information seeking behavior on statistical Websites: theoretical and design implications’ in Information access in the global economy:proceedings of the 61st annual meeting of the American society for Information ScienceOctober 25-29, 1998. Pittsburg, PA: pp. 303-314.

Hodge, Gail (2000). Systems of knowledge organisation for digital libraries: beyondtraditional authority files. The Digital Library Federation, Council on Library andInformation Resources: Washington, D.C., April 2000.

Hulser, Richard P. (2001). ‘Integrating technology into strategic planning’. Special LibrariesAssociation, Washington D.C. [Downloaded fromwww.sla.org/pubs/serial/io/1998/feb98/hulser.html on 31/5/2001]

Hurwitz Group. (1998). Enterprise Metadata Management. Hurwitz Group: Framingham,MA, December 1998.

Jennings, Mike. (2001). ‘The Generic meta data repository’ in DM Review Online January2001. [Downloaded fromwww.dmreview.com/editorial/dmreview/print_action.cfm?EdID=2954 on 31/5/2001]

Johnston, Tom. (2001). ‘Business rules, meta data and late binding, part 2’ in DM ReviewOnline February 2001. [Downloaded fromwww.dmreview.com/editorial/dmreview/print_action.cfm?EdID=3066 on 31/5/2001].

____________. (2001). ‘Business rules, meta data and late binding, part 3’ in DM ReviewOnline, February 2001. [Downloaded fromwww.dmreview.com/editorial/dmreview/print_action.cfm?EdID=3108 on 31/5/2001]

Kennedy, J., and Schauder, C. (1998). Records Management: A Guide To Corporate RecordKeeping. Addison Wesley Longman: Sydney.

Kurzweil, R. (1990). The Age of Intelligent Machines. MIT Press: Cambridge.

Larson, R. R. (1991). ‘Between Scylla and Charybdis: subject searching on the onlinecatalog’ in Advances in Librarianship 15: pp 175-236.

__________. (1991). ‘The Decline of subject searching: long term trends and patterns ofindex use in an online catalog’ in Journal of the American Society of InformationScience 42: pp 197-215.

Lesk, Michael. (1997). Practical Digital Libraries: Books, Bytes, and Bucks. San Francisco:Morgan Kaufmann Publishers.

Linden, A. and Jacobs, J. (2001). ‘How to swim, not sink, in the information flood’. ResearchNote, 25 May 2001. Gartner. [Downloaded from http://www.gartner.com on 17/7/2001]

Luther, Judy. (2001). White Paper on Electronic Journal Usage Statistics, Second edition.Council on Library and Information Resources: Washington, D.C. [Downloaded fromhttp://www.clir.org/pubs/abstract/pub94abst.html on 23/06/2001]

Marchionini, G. (1992). ‘Interfaces for end user information seeking’ in Journal of theAmerican Society of Information Science 43: pp 156-63.

Marco, David, 2001. ‘Meta data and data administration: implementing data quality throughmeta data, part 1’ in DM Review Online November 2000. [Downloaded fromwww.dmreview.com/editorial/dmreview/print_action.cfm?EdID=2525 on 17/7/2001]

Meredith, R., and Burstein, F. V., (2000). ‘Getting the Message Across with CommunicativeKnowledge Management’. Paper presented at the Australian Conference on KnowledgeManagement & Intelligent Decision Support, November 2000, Melbourne, Australia.

Meredith, R., May, D. and Piorun, J. (2000). Looking at Knowledge in Three Dimensions:An Holistic Approach to DSS Through Knowledge Management. Paper presented at theIFIP TC8/WG8.3 International Conference on Decision Support through KnowledgeManagement, 9-11 July, Stockholm, Sweden: pp 241-254.

Rich, E. (1989). ‘Stereotypes and user models’ in User models in dialogue systems. Eds. A.Kobsa and W. Wahlerster : Springer-Velag: pp 35-51.

Rothman, Joel B. (2000). ‘Establish an Effective Privacy Policy’ in e-Business Advisor(March): 34.

Rowley, J. (1994). ‘Revolution in current awareness services’ in Journal of Librarianshipand Information Science 26 (1) 1994: pp 7-14.

Russom, Philip. (1999). ‘New directions for knowledge management software’ in DM ReviewOnline October 1999. [Downloaded fromwww.dmreview.com/editorial/dmreview/print_action.cfm?EdID=1454 on 17/7/2001]

Salton, G. (1992).‘The state of retrieval systems evaluation’ in Information Processing andManagement 28 (4) 1992: pp 441-449.

Schauder, D. (2000): Postscript. In K. Williams (Ed.): Research Methods for Students andProfessionals: Information Management and Systems, Centre for Information Studies,Charles Sturt University: Wagga Wagga.

Sistla, Mala and Todd, James. (1998). ‘Warning: a killer mistake in business – don’t lettechnology define your requirements’. Special Libraries Association, Washington D.C.[Downloaded from www.sla.org/pubs/serial/io/1998/jun98/sistla.html on 31/5/2001]

Smiraglia, R. P. (1992). ‘Authority control and the extent of derivative relationships’. PhD.diss., University of Chicago.

St. Lifer, Evan and Older, Norman . (2001). ‘What public libraries must do to survive’ inLibrary Journal April 1, 2001. [Downloaded fromhttp://www.britannica.com/magazine/printcontent_id=218587 on 23/07/2001]

Stricker, Ulla de. (1998). ‘Marketing with a capital s : strategic planning for knowledge basedservices’. Special Libraries Association, Washington D.C. [Downloaded fromwww.sla.org/pubs/serial/io/1998/feb98/stricker.html on 31/5/2001]

Thomas, David H. (2000). ‘The Effect of interface design on item selection in an onlinecatalog’ in LRTS, 45 (1) 2000: pp 20-46.

Townley, Charles and Murray, Leigh. (1999). ‘Use-Based Criteria for Selecting andRetaining Electronic Information: A Case Study’ in Information Technology andLibraries 18 (1): pp 32–9.

Wang, Peiling, Hark, William B. and Tenopir, Carol. (2000). ‘User’s interaction with WorldWide Web resources: an exploratory study using a holistic approach’ in InformationProcessing and Management. 36 2000: pp 229-251

Zipperer, Lorri (1998) ‘Librarians in evolving corporate roles’. Special Libraries Association,Washington D.C. [Downloaded fromwww.sla.org.pubs.serial/io/1998/jun98/zipperer.html on 31/5/2001]